1. Field
This invention relates generally to adaptive controllers for controlling a process and more particularly to a self-tuning controller of the pattern-recognizing type in which controller operating parameters are changed automatically as required in response to differences occurring between the actual and desired states of the process so that controller behavior substantially matches process dynamics.
2. Description of the Prior Art
In a typical control loop, a controller is coupled to a process and a process controlled variable such as temperature, flow, or level is measured and fed back as a signal to the controller which compares that signal to a desired value known as the set point. Various controller elements respond to the error signal to generate a control signal for regulating the process so that the process controlled variable is maintained at the desired value. As can be understood, it is advantageous to have controller behavior substantially match the dynamics of a process so that the entire control loop can be maintained at its optimum state especially after the process has been disturbed or an abrupt change has been made to the set point.
A pattern-recognizing self-tuning controller automatically adjusts controller operating parameters so that controller behavior is changed as needed to keep the control loop in its optimum state. It should be understood that pattern recognition is a known technique used for manually tuning the operating parameters of a controller. Typically, the control system operating in a steady-state mode is perturbed and the pattern of the response is observed. A human operator compares that pattern to a desired pattern and modifies the controller settings so that two patterns are substantially matched. Tuning can thus be time consuming and costly if many trial-and-error attempts occur before the requisite experience and/or knowledge of the process is gained for setting the controller operating parameters.
Moreover, since controller settings are for a particular set and range of operating conditions, manual retuning will be needed to compensate for changes in the operating conditions which may be the result of occurrences such as set point revisions, process load disturbances, or age, wear and corrosion of control system equipment. Various attempts have been made with limited success to provide an adaptive controller which eliminates the need for but duplicates the manual tuning process used by a skilled human operator.
For many applications, the equations which describe the dynamic behavior of the control loop are very complex so that it is very difficult to determine analytically what operating parameters should be used for achieving the desired ideal pattern. As a result, analytical solutions are oftentimes based on simplifying assumptions that reduce the range of operating conditions or the number of process applications which can be controlled without human intervention.
In U.S. Pat. No. 3,798,426 issued to E. H. Bristol and assigned to the present assignee, a pattern-evaluating adaptive controller is disclosed which is capable of being tuned without a human operator. As described in the patent, when the process being controlled is recovering from an upset such as a local disturbance or a change in set point, the controller made according to the Bristol teaching examines the initial recovery behavior of the process controlled variable and calculates various evaluation time intervals. Deviations of the process controlled variable from its desired value are preferably integrated over each of the evaluation intervals and combined to produce an integrated error. Based on the size of the integrated error, the operating parameters of the controller are changed as needed for insuring optimal control action when the process is next upset.
However, the relationship between the initial recovery behavior and the size of the associated evaluation intervals does not always remain constant for all operating situations. Although the controller taught by Bristol is suitable for controlling a complicated non-linear process, there are limits to the number of situations that can be managed before a human operator is required to change the criteria used for determining the evaluation intervals.
Accordingly, there is a need for an improved adaptive controller which is suitable for a wide range of operating conditions and/or applications. Moreover, it is desirable to minimize or eliminate the services of a human operator especially in situations where that operator faces physical dangers.